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Background: Although modern Australian healthcare systems provide patient-centred care, the ability to predict and prevent suboptimal post-procedural outcomes based on patient demographics at admission may improve health equity. This study aimed to identify patient demographic characteristics that might predict disparities in mortality, readmission, and discharge outcomes after either an operative or non-operative procedural hospital admission., Methods: This retrospective cohort study included all surgical and non-surgical procedural admissions at three of the four major metropolitan public hospitals in South Australia in 2022. Multivariable logistic regression, with backwards selection, evaluated association between patient demographic characteristics and outcomes up to 90 days post-procedurally., Results: 40 882 admissions were included. Increased likelihood of all-cause, post-procedure mortality in-hospital, at 30 days, and 90 days, were significantly associated with increased age (P < 0.001), increased comorbidity burden (P < 0.001), an emergency admission (P < 0.001), and male sex (P = 0.046, P = 0.03, P < 0.001, respectively). Identification as ATSI (P < 0.001) and being born in Australia (P = 0.03, P = 0.001, respectively) were associated with an increased likelihood of 30-day hospital readmission and decreased likelihood of discharge directly home, as was increased comorbidity burden (P < 0.001) and emergency admission (P < 0.001). Being married (P < 0.001) and male sex (P = 0.003) were predictive of an increased likelihood of discharging directly home; in contrast to increased age (P < 0.001) which was predictive of decreased likelihood of this occurring., Conclusions: This study characterized several associations between patient demographic factors present on admission and outcomes after surgical and non-surgical procedures, that can be integrated within patient flow pathways through the Australian healthcare system to improve healthcare equity., (© 2024 The Authors. ANZ Journal of Surgery published by John Wiley & Sons Australia, Ltd on behalf of Royal Australasian College of Surgeons.)

Introduction: Readmission is a poor outcome for both patients and healthcare systems. The association of certain sociocultural and demographic characteristics with likelihood of readmission is uncertain in general surgical patients., Method: A multi-centre retrospective cohort study of consecutive unique individuals who survived to discharge during general surgical admissions was conducted. Sociocultural and demographic variables were evaluated alongside clinical parameters (considered both as raw values and their proportion of change in the 1-2 days prior to admission) for their association with 7 and 30 days readmission using logistic regression., Results: There were 12,701 individuals included, with 304 (2.4%) individuals readmitted within 7 days, and 921 (7.3%) readmitted within 30 days. When incorporating absolute values of clinical parameters in the model, age was the only variable significantly associated with 7-day readmission, and primary language and presence of religion were the only variables significantly associated with 30-day readmission. When incorporating change in clinical parameters between the 1-2 days prior to discharge, primary language and religion were predictive of 30-day readmission. When controlling for changes in clinical parameters, only higher comorbidity burden (represented by higher Charlson comorbidity index score) was associated with increased likelihood of 30-day readmission., Conclusions: Sociocultural and demographic patient factors such as primary language, presence of religion, age, and comorbidity burden predict the likelihood of 7 and 30-day hospital readmission after general surgery. These findings support early implementation a postoperative care model that integrates all biopsychosocial domains across multiple disciplines of healthcare., (© 2023. Crown.)

Background: This study aimed to examine the accuracy with which multiple natural language processing artificial intelligence models could predict discharge and readmissions after general surgery., Methods: Natural language processing models were derived and validated to predict discharge within the next 48 hours and 7 days and readmission within 30 days (based on daily ward round notes and discharge summaries, respectively) for general surgery inpatients at 2 South Australian hospitals. Natural language processing models included logistic regression, artificial neural networks, and Bidirectional Encoder Representations from Transformers., Results: For discharge prediction analyses, 14,690 admissions were included. For readmission prediction analyses, 12,457 patients were included. For prediction of discharge within 48 hours, derivation and validation data set area under the receiver operator characteristic curves were, respectively: 0.86 and 0.86 for Bidirectional Encoder Representations from Transformers, 0.82 and 0.81 for logistic regression, and 0.82 and 0.81 for artificial neural networks. For prediction of discharge within 7 days, derivation and validation data set area under the receiver operator characteristic curves were, respectively: 0.82 and 0.81 for Bidirectional Encoder Representations from Transformers, 0.75 and 0.72 for logistic regression, and 0.68 and 0.67 for artificial neural networks. For readmission prediction within 30 days, derivation and validation data set area under the receiver operator characteristic curves were, respectively: 0.55 and 0.59 for Bidirectional Encoder Representations from Transformers and 0.77 and 0.62 for logistic regression., Conclusion: Modern natural language processing models, particularly Bidirectional Encoder Representations from Transformers, can effectively and accurately identify general surgery patients who will be discharged in the next 48 hours. However, these approaches are less capable of identifying general surgery patients who will be discharged within the next 7 days or who will experience readmission within 30 days of discharge., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The frequency of oxycodone adverse reactions, subsequent opioid prescription, effect on pain and patient care in general surgery patients are not well known. This study aimed to determine prevalence of documented oxycodone allergy and intolerances (independent variables) in a general surgical cohort, and association with prescribing other analgesics (particularly opioids), subjective pain scores, and length of hospital stay (dependent variables)., Methods: This retrospective cohort study included general surgery patients from two South Australian hospitals between April 2020 and March 2022. Multivariable logistic regression evaluated associations between previous oxycodone allergies and intolerances, prescription records, subjective pain scores, and length of hospital stay., Results: Of 12 846 patients, 216 (1.7%) had oxycodone allergies, and 84 (0.7%) oxycodone intolerances. The 216 oxycodone allergy patients had lower odds of receiving oxycodone (OR 0.17, P < 0.001), higher odds of tramadol (OR 3.01, P < 0.001) and tapentadol (OR 2.87, P = 0.001), but 91 (42.3%) still received oxycodone and 19 (8.8%) morphine. The 84 with oxycodone intolerance patients had lower odds of receiving oxycodone (OR 0.23, P < 0.001), higher odds of fentanyl (OR 3.6, P < 0.001) and tramadol (OR 3.35, P < 0.001), but 42 (50%) still received oxycodone. Patients with oxycodone allergies and intolerances had higher odds of elevated subjective pain (OR 1.60, P = 0.013; OR 2.36, P = 0.002, respectively) and longer length of stay (OR 1.36, P = 0.038; OR 2.24, P = 0.002, respectively) than patients without these., Conclusions: General surgery patients with oxycodone allergies and intolerances are at greater risk of worse postoperative pain and longer length of stay, compared to patients without. Many still receive oxycodone, and other opioids that could cause cross-reactivity., (© 2023 The Authors. ANZ Journal of Surgery published by John Wiley & Sons Australia, Ltd on behalf of Royal Australasian College of Surgeons.)

Background: The applicability of the vital signs prompting medical emergency response (MER) activation has not previously been examined specifically in a large general surgical cohort. This study aimed to characterize the distribution, and predictive performance, of four vital signs selected based on Australian guidelines (oxygen saturation, respiratory rate, systolic blood pressure and heart rate); with those of the MER activation criteria., Methods: A retrospective cohort study was conducted including patients admitted under general surgical services of two hospitals in South Australia over 2 years. Likelihood ratios for patients meeting MER activation criteria, or a vital sign in the most extreme 1% for general surgery inpatients (<0.5th percentile or > 99.5th percentile), were calculated to predict in-hospital mortality., Results: 15 969 inpatient admissions were included comprising 2 254 617 total vital sign observations. The 0.5th and 99.5th centile for heart rate was 48 and 133, systolic blood pressure 85 and 184, respiratory rate 10 and 31, and oxygen saturations 89% and 100%, respectively. MER activation criteria with the highest positive likelihood ratio for in-hospital mortality were heart rate ≤ 39 (37.65, 95% CI 27.71-49.51), respiratory rate ≥ 31 (15.79, 95% CI 12.82-19.07), and respiratory rate ≤ 7 (10.53, 95% CI 6.79-14.84). These MER activation criteria likelihood ratios were similar to those derived when applying a threshold of the most extreme 1% of vital signs., Conclusions: This study demonstrated that vital signs within Australian guidelines, and escalation to MER activation, appropriately predict in-hospital mortality in a large cohort of patients admitted to general surgical services in South Australia., (© 2023 The Authors. ANZ Journal of Surgery published by John Wiley & Sons Australia, Ltd on behalf of Royal Australasian College of Surgeons.)

Background: This study aimed to examine the performance of machine learning algorithms for the prediction of discharge within 12 and 24 h to produce a measure of readiness for discharge after general surgery., Methods: Consecutive general surgery patients at two tertiary hospitals, over a 2-year period, were included. Observation and laboratory parameter data were stratified into training, testing and validation datasets. Random forest, XGBoost and logistic regression models were evaluated. Each ward round note time was taken as a different event. Primary outcome was classification accuracy of the algorithmic model able to predict discharge within the next 12 h on the validation data set., Results: 42 572 ward round note timings were included from 8826 general surgery patients. Discharge occurred within 12 h for 8800 times (20.7%), and within 24 h for 9885 (23.2%). For predicting discharge within 12 h, model classification accuracies for derivation and validation data sets were: 0.84 and 0.85 random forest, 0.84 and 0.83 XGBoost, 0.80 and 0.81 logistic regression. For predicting discharge within 24 h, model classification accuracies for derivation and validation data sets were: 0.83 and 0.84 random forest, 0.82 and 0.81 XGBoost, 0.78 and 0.79 logistic regression. Algorithms generated a continuous number between 0 and 1 (or 0 and 100), representing readiness for discharge after general surgery., Conclusions: A derived artificial intelligence measure (the Adelaide Score) successfully predicts discharge within the next 12 and 24 h in general surgery patients. This may be useful for both treating teams and allied health staff within surgical systems., (© 2023 The Authors. ANZ Journal of Surgery published by John Wiley & Sons Australia, Ltd on behalf of Royal Australasian College of Surgeons.)

Background: Endoscopic retrograde cholangiopancreatography (ERCP) is a commonly performed procedure worldwide. The aim of this study was to examine cases of mortality after ERCP to identify clinical incidents that are potentially preventable, to improve patient safety., Methods: The Australian and New Zealand Audit of Surgical Mortality provides an independent and externally peer-reviewed audit of surgical mortality pertaining to potentially avoidable issues. A retrospective review of prospectively collected data within this database was performed for the 8-year audit period from 1 January 2009 to 31 December 2016. Clinical incidents were identified by assessors through first- or second-line review, and thematically coded into periprocedural stages. These themes were then qualitatively analysed., Results: There were 58 potentially avoidable deaths following ERCP, with 85 clinical incidents. Preprocedural incidents were most common (n = 37), followed by postprocedural (n = 32) and then intraprocedural (n = 8). Communication issues occurred across the periprocedural period (n = 8). Preprocedural incidents included delay to procedure, inadequate resuscitative management, decision to perform procedure and inadequate assessment. Intraprocedural incidents comprised technical factors and inadequate support. Postprocedural incidents involved inappropriate treatment, delay in definitive surgical treatment or in recognizing complications, inappropriate second-line intervention and inadequate assessment. Communication incidents comprised inadequate documentation, failure to escalate care and poor inter-clinician communication., Conclusion: Causes of mortality following ERCP are wide-ranging, and reviewing clinical incidents associated with potentially avoidable mortality can serve to inform and educate practitioners. In collating a subset of cases in which procedure-related mortality was deemed avoidable, a series of cautionary tales about ERCP is presented that may provide cues to practitioners on improving patient safety and inform future surgical practice., (© 2023 The Authors. ANZ Journal of Surgery published by John Wiley & Sons Australia, Ltd on behalf of Royal Australasian College of Surgeons.)

Background: Depression is the leading cause of global disability and can develop following the change in body image and functional capacity associated with stoma surgery. However, reported prevalence across the literature is unknown. Accordingly, we performed a systematic review and meta-analysis aiming to characterise depressive symptoms after stoma surgery and potential predictive factors., Methods: PubMed/MEDLINE, Embase, CINAHL and Cochrane Library were searched from respective database inception to 6 March 2023 for studies reporting rates of depressive symptoms after stoma surgery. Risk of bias was assessed using the Downs and Black checklist for non-randomised studies of interventions (NRSIs), and Cochrane RoB2 tool for randomised controlled trials (RCTs). Meta-analysis incorporated meta-regressions and a random-effects model., Registration: PROSPERO, CRD42021262345., Results: From 5,742 records, 68 studies were included. According to Downs and Black checklist, the 65 NRSIs were of low to moderate methodological quality. According to Cochrane RoB2, the three RCTs ranged from low risk of bias to some concerns of bias. Thirty-eight studies reported rates of depressive symptoms after stoma surgery as a proportion of the respective study populations, and from these, the median rate across all timepoints was 42.9% 42.9% (IQR: 24.2-58.9%). Pooled scores for respective validated depression measures (Hospital Anxiety and Depression Score (HADS), Beck Depression Inventory (BDI), and Patient Health Questionnaire-9 (PHQ-9)) across studies reporting those scores were below clinical thresholds for major depressive disorder according to severity criteria of the respective scores. In the three studies that used the HADS to compare non-stoma versus stoma surgical populations, depressive symptoms were 58% less frequent in non-stoma populations. Region (Asia-Pacific; Europe; Middle East/Africa; North America) was significantly associated with postoperative depressive symptoms (p = 0.002), whereas age (p = 0.592) and sex (p = 0.069) were not., Conclusions: Depressive symptoms occur in almost half of stoma surgery patients, which is higher than the general population, and many inflammatory bowel disease and colorectal cancer populations outlined in the literature. However, validated measures suggest this is mostly at a level of clinical severity below major depressive disorder. Stoma patient outcomes and postoperative psychosocial adjustment may be enhanced by increased psychological evaluation and care in the perioperative period., (© 2023. The Author(s).)

Background: Optimal timing and modality of surveillance post hepatectomy for colorectal cancer liver metastases (CLM) has not been established. Recommendations vary between countries and surgical units. Individual clinicians do not always adhere to guidelines., Methods: Using a prospectively collected database of consecutive hepatectomy patients at The Queen Elizabeth Hospital in Adelaide, Australia, CLM patients were reviewed for evidence of recurrent disease (20 February 1996-30 June 2018). Timing and modality of disease detection was analysed. Follow up was until 30 June 2020 or death., Results: 244 patients underwent hepatectomy for CLM during the study period. 139 patients (57%) experienced recurrence post initial hepatectomy (mean time 13.2 months; range 0.6-84.7). For all hepatic recurrences (n = 172), majority of disease was detected in the first seven months post hepatectomy (55%) and by four years, 97.7% of recurrent disease was detected. 51 patients underwent curative repeat hepatectomy after recurrence was detected. Nearly all disease was detected via surveillance CT (160/172; 93%); 12 patients presented with clinical symptoms., Conclusion: Hepatectomy patients are likely to experience recurrent disease and clinicians must ensure a robust surveillance plan is in place. We recommend a triple-phase CT at 6, 12, 18, 24, 36 and 48 months., (Copyright © 2022 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.)

Background: Interhospital transfers in Australia facilitate access to acute surgical services, however transfer delays can occur. The aims of this study were to examine Australian mortality audit data on acute surgical patients who were transferred after presenting with a surgical emergency, and to identify modifiable predictors of transfer delay., Methods: Surgical admissions between 1 January 2001 and 18 August 2020 were retrospectively extracted from the Australian and New Zealand Audit of Surgical Mortality database. Relevant factors and themes of interest were collated. Results were presented as odds ratios (OR) and 95% confidence intervals (CI), with statistical significance defined as P <0.05., Results: After exclusion, a final 8270 cases were analysed. Non-modifiable predictors identified were female gender (OR 1.34, 95% CI 1.05-1.70, P = 0.0184), comorbidities (OR 1.50, 95% CI 1.40-161, P <0.0001) and major non-trauma non-vascular specialty (OR 1.54 to 7.77, depending on specialty, P < 0.05). Modifiable predictors were inadequate clinical assessment (OR 49.48, 95% CI 32.91-74.38, P <0.0001), poor communication (OR 6.62, 95% CI 3.70-11.85, P <0.0001) and multiple transfers (OR 6.30, OR 95% 4.31-9.21, P <0.0001). Age, lack of bed and after-hours transfer did not predict transfer delays. Metropolitan transfers was protective against transfer delays (OR 0.64, 95% CI 0.47-0.86, P = 0.0035)., Conclusion: In the view of the receiving surgeon or assessor, all transfer delays potentially contributed to patient deaths, and may have been preventable. Strategies directed at modifiable factors could minimize delays. Increased surgical services in non-metropolitan regions could reduce need for transfer. Prospective data is required to examine if the same predictors are observed in surgical patients who survive., (© 2022 Royal Australasian College of Surgeons.)

Background: Emergency general surgery is an emerging public health issue globally, with substantial healthcare burden. Interhospital transfer of critically unwell surgical patients has been the mainstay of bridging gaps in surgical coverage in regional and rural locations, despite evidence of greater morbidity and mortality. Delays in transfer invariably occurs and compounds the situation. Our aim was to examine the factors influencing interhospital transfer delays in emergency general surgical patients., Methods: A systematic search of PubMED and EmBase, was performed by two researchers from 2020 to 23rd Feb 2021, for English articles related to interhospital transfer delays in emergency general surgical patients, with an age of >16. Articles were critically appraised and data were extracted into a pre-specified data extraction form. No data was suitable for statistical analysis and a narrative synthesis was performed instead., Results: Six relevant articles were identified from the search. All studies were retrospective cohort studies with moderate to high risk of bias. Lack of consultant surgeon input, after hours transfer, need for intensive care bed and poor transfer documentation may have a role in interhospital transfer delays. Patients with public health insurance, multiple comorbidities and non-emergency medical conditions experience longer transfer request time and may be at risk of precipitating interhospital transfer delays. Transfer delays are seen in transfers over longer distances., Conclusion: There is a paucity of knowledge on what and how factors influence interhospital transfer delays in emergency general surgical patients. Well-designed prospective cohort studies are required to bridge this knowledge gap., (© 2022 Royal Australasian College of Surgeons.)